Package: kernelshap
Title: Kernel SHAP
Version: 0.1.0
Authors@R: 
    person("Michael", "Mayer", , "mayermichael79@gmail.com", role = c("aut", "cre"))
Description: Implementation of the model-agnostic Kernel SHAP algorithm by
    Ian Covert and Su-In Lee (2021)
    <http://proceedings.mlr.press/v130/covert21a>.  Due to its iterative
    nature, standard errors of the SHAP values are provided and
    convergence is monitored.  The package allows to work with any model
    that provides numeric predictions.  Examples include linear
    regression, logistic regression (logit or probability scale), other
    generalized linear models, generalized additive models, and neural
    networks. The package plays well together with meta-learning packages
    like 'caret' or 'mlr3'. Visualizations can be done using the R package
    'shapviz'.
License: GPL (>= 2)
Depends: R (>= 3.2.0)
Encoding: UTF-8
RoxygenNote: 7.1.2
Imports: stats, utils
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2022-08-09 19:40:11 UTC; Michael
Author: Michael Mayer [aut, cre]
Maintainer: Michael Mayer <mayermichael79@gmail.com>
Repository: CRAN
Date/Publication: 2022-08-12 12:20:06 UTC
